XStruct:从多个大型XML文档中高效提取模式

J. Hegewald, Felix Naumann, Melanie Herschel
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引用次数: 80

摘要

XML实际上是Web上数据交换的标准格式。虽然生成XML数据相当简单,但是设计一个模式并保证根据该模式生成的数据是有效的,这是一项复杂的任务。因此,许多XML数据没有模式,或者没有模式。为了获得拥有模式的好处——XML数据的高效查询和存储、语义验证、数据集成等——必须提取该模式。在本文中,我们提出了一种用于XML模式提取的自动技术XStruct。基于[5]的思想,XStruct通过应用几种启发式方法来推导正则表达式来提取XML数据的模式,这些正则表达式是1-明确的,并且正确地描述了每个元素的内容,但是泛化到一个合理的程度。与已知技术相比,我们的方法有几个优点:XStruct在时间和内存消耗方面都可以扩展到非常大的文档(超过1GB);它能够为多个文档提取一个通用的、完整的、正确的、最小的和可理解的模式;它检测数据类型和属性。实验证实了这些特征和性质。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
XStruct: Efficient Schema Extraction from Multiple and Large XML Documents
XML is the de facto standard format for data exchange on the Web. While it is fairly simple to generate XML data, it is a complex task to design a schema and then guarantee that the generated data is valid according to that schema. As a consequence much XML data does not have a schema or is not accompanied by its schema. In order to gain the benefits of having a schema - efficient querying and storage of XML data, semantic verification, data integration, etc.- this schema must be extracted. In this paper we present an automatic technique, XStruct, for XML Schema extraction. Based on ideas of [5], XStruct extracts a schema for XML data by applying several heuristics to deduce regular expressions that are 1-unambiguous and describe each element’s contents correctly but generalized to a reasonable degree. Our approach features several advantages over known techniques: XStruct scales to very large documents (beyond 1GB) both in time and memory consumption; it is able to extract a general, complete, correct, minimal, and understandable schema for multiple documents; it detects datatypes and attributes. Experiments confirm these features and properties.
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